矿区沉陷DEM多重滤波方法研究OACSTPCD

Aiming at the problems of long cycle time and large workload of traditional surface movement monitoring methods,the method of acquiring ground point clouds and constructing subsidence DEM through UAV LiDAR and point cloud filtering enables surface subsidence monitoring fast and efficient.Because of the subsidence DEM models constructed by existing point cloud filter-ing and interpolation algorithms still cover noise,which limits the popularity of this technology in mining areas,therefore,it is signi-ficant to further study the removal method of subsidence DEM noise,compare and analyze the multiple filtering and classical filter-ing techniques.Experimental analysis results show that the median filter combined with Wiener filter has the best denoising effect among several denoising methods,which can keep the details of the subsidence basin and meet the basic requirements of surface de-formation monitoring in mining areas.